We propose a cross-layer-model based adaptive resource-allocation scheme for the diverse quality-of-service (QoS) guarantees over downlink mobile wireless networks. Our proposed scheme dynamically assigns power-levels and timeslots for heterogeneous real-time mobile users to satisfy the variation of statistical delay-bound QoS requirements. To achieve this goal, we apply Wu and Negi’s effective capacity approach to derive the admission-control and power/time-slot allocation algorithms, guaranteeing the statistical delay-bound for heterogeneous mobile users. When designing such an algorithm, we study the impact of physical-layer issues such as adaptive power-control and channel-state information (CSI) feedback delay on the QoS provisioning performance. Through numerical and simulation results, we observe that the adaptive power adaptation has a significant impact on statistical QoS-guarantees. In addition, the analyses indicate that our proposed resource-allocation algorithms are shown to be able to efficiently support the diverse QoS requirements for various real-time mobile users over different wireless channels. Also, in an in-door mobile environment, e.g., the widely used wireless local-area networks (WLAN), our proposed algorithm is shown to be robust to the CSI feedback delay.

We propose a physical-datalink cross-layer resource allocation scheme over wireless relay networks for quality-ofservice (QoS) guarantees. By integrating information theory with the concept of effective capacity, our proposed scheme aims at maximizing the relay network throughput subject to a given delay QoS constraint. This delay constraint is characterized by the socalled QoS exponent θ, which is the only requested information exchanged between the physical layer and the datalink layer in our cross-layer design based scheme. Over both amplify-and-forward (AF) and decode-and-forward (DF) relay networks, we develop the associated dynamic resource allocation algorithms for wireless multimedia communications. Over DF relay network, we also study a fixed power allocation scheme to provide QoS guarantees. The simulations and numerical results verify that our proposed cross-layer resource allocation can efficiently support diverse QoS requirements over wireless relay networks. Both AF and DF relays show significant superiorities over direct transmissions when the delay QoS constraints are stringent. On the other hand, our results demonstrate the importance of deploying the dynamic resource allocation for stringent delay QoS guarantees.

Abstract — 1 Energy efficiency in fading channels in the pres-ence of QoS constraints is studied. Effective capacity, which provides the maximum constant arrival rate that a given process can support while satisfying statistical delay constraints, is considered. Spectral efficiency–bit energy tradeoff is analyzed in the low-power and wideband regimes by employing the effective capacity formulation, rather than the Shannon capacity, and energy requirements under QoS constraints are identified. The analysis is conducted for the case in which perfect channel side information (CSI) is available at the receiver and also for the case in which perfect CSI is available at both the receiver and transmitter. In particular, it is shown in the low-power regime that the minimum bit energy required in the presence of QoS constraints is the same as that attained when there are no such limitations. However, this performance is achieved as

Abstract—Due to the time-varying wireless channels, deterministic quality of service (QoS) is usually difficult to guarantee for real-time multi-layer video transmissions in wireless networks. Consequently, statistical QoS guarantees have become an important alternative in supporting real-time video transmissions. In this paper, we propose an efficient framework to model the statistical delay QoS guarantees, in terms of QoS exponent, effective bandwidth/capacity, and delay-bound violation probability, for multi-layer video transmissions over wireless fading channels. In particular, a separate queue is maintained for each video layer, and the same delay bound and corresponding violation probability threshold are set up for all layers. Applying the effective bandwidth/capacity analyses on the incoming video stream, we obtain a set of QoS exponents for all video layers to effectively characterize this delay QoS requirement. We then develop a set of optimal adaptive transmission schemes to minimize the resource consumption while satisfying the diverse QoS requirements under various scenarios, including video unicast/multicast with and/or without loss tolerance. Simulation results are also presented to demonstrate the impact of statistical QoS provisionings on resource allocations of our proposed adaptive transmission schemes. Index Terms—Mobile multicast, wireless networks, rate control, layered video streaming, statistical QoS guarantees. I.

Transmission over wireless fading channels under quality of service (QoS) constraints is studied when only the receiver has channel side information. Being unaware of the channel conditions, transmitter is assumed to send the information at a fixed rate. Under these assumptions, a two-state (ON-OFF) transmission model is adopted, where information is transmitted reliably at a fixed rate in the ON state while no reliable transmission occurs in the OFF state. QoS limitations are imposed as constraints on buffer violation probabilities, and effective capacity formulation is used to identify the maximum throughput that a wireless channel can sustain while satisfying statistical QoS constraints. Energy efficiency is investigated by obtaining the bit energy required at zero spectral efficiency and the wideband slope in both wideband and low-power regimes assuming that the receiver has perfect channel side information (CSI). In the wideband regime, it is shown that the bit energy required at zero spectral efficiency is the minimum bit energy. A similar result is shown for a certain class of fading distributions in the low-power regime. In both wideband and lowpower regimes, the increased energy requirements due to the presence of QoS constraints are quantified. Comparisons with variable-rate/fixed-power and variable-rate/variable-power cases are given. Energy efficiency is further analyzed in the presence of channel uncertainties. The scenario in which a priori unknown fading coefficients are estimated at the receiver via minimum mean-square-error (MMSE) estimation with the aid of training symbols, is considered. The optimal fraction of power allocated to training is identified under QoS constraints. It is proven that the minimum bit energy in the low-power regime is attained at a certain nonzero power level below which bit energy increases without bound with vanishing power. Hence, it is shown that it is extremely energy inefficient to operate at very low power levels when the channel is only imperfectly known.

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The next generation wireless networks call for quality of service (QoS) support. The effective capacity (EC) proposed by Wu and Negi provides a powerful tool for the design of QoS provisioning mechanisms. In their previous work, Wu and Negi derived a formula for effective capacity of a Rayleigh fading channel with arbitrary Doppler spectrum. However, their paper did not provide simulation results to verify the accuracy of the EC formula derived in their paper. This is due to difficulty in simulating a Rayleigh fading channel with a Doppler spectrum of continuous frequency, required by the EC formula. To address this difficulty, we develop a verification methodology based on a new discrete-frequency EC formula; different from the EC formula developed by Wu and Negi, our new discrete-frequency EC formula can be used in practice. Through simulation, we verify that the EC formula developed by Wu and Negi is accurate. Furthermore, to facilitate the application of the EC theory to the design of practical QoS provisioning mechanisms in wireless networks, we propose a spectral-estimation-based algorithm to estimate the EC function, given channel measurements; we also analyze the effect of spectral estimation error on the accuracy of EC estimation. Simulation results show that our proposed spectral-estimation-based EC estimation algorithm is accurate, indicating the excellent practicality of our algorithm.

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Abstract—The distributed multiple-input-multiple-output (MIMO) techniques across multiple cooperative base stations (BS) can significantly enhance the capability of the broadband wireless networks in terms of quality-of-service (QoS) provisioning for wireless data transmissions. However, the computational complexity and the interfering range of the distributed MIMO systems also increase rapidly as the number of cooperative BS’s increases. In this paper, we propose the QoS-aware BS-selection schemes for the distributed wireless MIMO links, which aim at minimizing the BS usages and reducing the interfering range, while satisfying diverse statistical delay-QoS constraints characterized by the delay-bound violation probability and the effective capacity technique. In particular, based on the channel state information (CSI) and QoS requirements, a subset of BS with variable cardinality for

The grail of next-generation wireless networks is providing real-time services for delay-sensitive applications, which require that the wireless networks provide QoS guarantees. The effective capacity (EC) proposed by Wu and Negi provides a powerful tool for design of QoS provisioning mechanisms. In this paper, we intend to generalize their formula for the effective capacity of a correlated Rayleigh fading channel; specifically, we derive a closed form approximate EC formula for a special correlated Nakagami-m fading channel, for which the inverse of the correlation coefficient matrix is tridiagonal. To verify its accuracy via simulation, we develop a Green-matrix based approach, which allows us to analytically obtain the effective capacity (given the joint probability density function of a correlated Nakagami-m fading channel) while being able to simulate the corresponding channel gain process. Simulation results show that our EC formula is accurate. Furthermore, to facilitate the application of the EC theory to the design of practical QoS provisioning mechanisms, we propose a simple algorithm for estimating the EC of an arbitrary correlated Nakagami-m fading channel, given channel measurements; simulation results demonstrate the accuracy of our proposed EC estimation algorithm, showing its suitability in practice.